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An Adaptive Hierarchical Model Based on Fusion of Ontology and Context
Pages: 885-889
Year: Issue:  10
Journal: Transactions of Beijing Institute of Technology

Keyword:  增量学习上下文本体层次分类;
Abstract: 提出一种新的自适应层次分类(HAC)模型,通过本体对特征集进行语义扩展,并以增量形式在层次模型中构建特征上下文和类别相关上下文,以辅助实现一种高效、无阻滞的层次分类. 实验结果证明,模型HAC具有相对更好的分类性能,而且分类速度更快,有利于实现实时在线的文档分类.
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